---
title: "Who cites Sahar Kazemzadeh — 375 papers of our library"
description: "375 papers of the Elamur Research library cite the works of Sahar Kazemzadeh, found in their bibliographies; the most cited first."
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---
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# Who cites Sahar Kazemzadeh

375 citations of their works from 375 papers of our library (of the 149,439 whose bibliographies we read) · 87 with a page here, the most cited first · [← Sahar Kazemzadeh](https://md.research.elamur.ai/free/en/authors/sahar-kazemzadeh/)

1. **[Improved Baselines with Visual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/liu-2023-improved-baselines-visual-instruction-tuning/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Haotian Liu, Chunyuan Li, Yuheng Li, et al.*2023 · 2,614 citations*
2. **[UNITER: UNiversal Image-TExt Representation Learning](https://md.research.elamur.ai/free/en/papers/chen-2019-uniter-universal-image-text-representation/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yen-Chun Chen, Linjie Li, Licheng Yu, et al.*2019 · 2,418 citations*
3. [**ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks arXiv:1908.02265**Jiasen Lu, Dhruv Batra, Devi Parikh, et al.*2019 · 2,302 citations*](https://md.research.elamur.ai/free/en/papers/lu-2019-vilbert-pretraining-task-agnostic-visiolinguistic/)
4. [**VisualBERT: A Simple and Performant Baseline for Vision and Language arXiv:1908.03557**Liunian Harold Li, Mark Yatskar, Da Yin, et al.*2019 · 1,568 citations*](https://md.research.elamur.ai/free/en/papers/li-2019-visualbert-simple-performant-baseline-vision/)
5. **[Generation and Comprehension of Unambiguous Object Descriptions](https://md.research.elamur.ai/free/en/papers/mao-2015-generation-comprehension-unambiguous-object-descriptions/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Junhua Mao, Jonathan Huang, Alexander Toshev, et al.*2015 · 1,388 citations*
6. **[Modeling Context in Referring Expressions](https://md.research.elamur.ai/free/en/papers/yu-2016-modeling-context-referring-expressions/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Licheng Yu, Patrick Poirson, Shan Yang, et al.*2016 · 1,203 citations*
7. [**MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models arXiv:2304.10592**Deyao Zhu, Jun Chen, Xiaoqian Shen, et al.*2023 · 1,141 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-minigpt-4-enhancing-vision-language/)
8. [**VL-BERT: Pre-training of Generic Visual-Linguistic Representations arXiv:1908.08530**Weijie Su, Xizhou Zhu, Yue Cao, et al.*2019 · 1,066 citations*](https://md.research.elamur.ai/free/en/papers/su-2019-vl-bert-pre-training-generic/)
9. [**Qwen2.5-VL Technical Report arXiv:2502.13923**Shuai Bai, Keqin Chen, Xuejing Liu, et al.*2025 · 1,031 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen2-5-vl-technical/)
10. **[MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 1,005 citations*
11. [**Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond arXiv:2308.12966**Jinze Bai, Shuai Bai, Shusheng Yang, et al.*2023 · 970 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-vl-versatile-vision-language/)
12. [**Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution arXiv:2409.12191**Peng Wang, Shuai Bai, Sinan Tan, et al.*2024 · 860 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-qwen2-vl-enhancing-vision/)
13. [**A Corpus for Reasoning About Natural Language Grounded in Photographs (NLVR2)**Alane Suhr, Stephanie Zhou, Ally Zhang, et al.*2019 · 670 citations*](https://md.research.elamur.ai/free/en/papers/suhr-2019-corpus-reasoning-natural-language-grounded/)
14. [**CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning arXiv:1612.06890**Justin Johnson, Bharath Hariharan, Laurens van der Maaten, et al.*2016 · 464 citations*](https://md.research.elamur.ai/free/en/papers/johnson-2016-clevr-diagnostic-dataset-compositional-language/)
15. **[ShareGPT4V: Improving Large Multi-Modal Models with Better Captions](https://md.research.elamur.ai/free/en/papers/chen-2023-sharegpt4v-improving-large-multi-modal/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Lin Chen, Jinsong Li, Xiaoyi Dong, et al.*2023 · 454 citations*
16. [**The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes arXiv:2005.04790**Douwe Kiela, Hamed Firooz, Aravind Mohan, et al.*2020 · 420 citations*](https://md.research.elamur.ai/free/en/papers/kiela-2020-hateful-memes-challenge-detecting-hate/)
17. [**Yi: Open Foundation Models by 01.AI arXiv:2403.04652**Alex Young, Bei Chen, Chao Li, et al.*2024 · 408 citations*](https://md.research.elamur.ai/free/en/papers/ai-2024-yi-open-foundation-models-01/)
18. **[CogVLM: Visual Expert for Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-cogvlm-visual-expert-pretrained/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Weihan Wang, Qingsong Lv, Wenmeng Yu, et al.*2023 · 383 citations*
19. [**Qwen3-VL Technical Report arXiv:2511.21631**Shuai Bai, Yuxuan Cai, Ruizhe Chen, et al.*2025 · 370 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen3-vl-technical-report/)
20. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 320 citations*
21. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling arXiv:2412.05271**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 287 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/)
22. **[LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-llama-vid-image-worth-2/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yanwei Li, Chengyao Wang, Jiaya Jia*2023 · 262 citations*
23. [**Qwen2.5-Omni Technical Report arXiv:2503.20215**Jin Xu, Zhifang Guo, Jinzheng He, et al.*2025 · 227 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-qwen2-5-omni-technical/)
24. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models arXiv:2504.10479**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
25. [**Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic arXiv:2306.15195**Keqin Chen, Zhao Zhang, Weili Zeng, et al.*2023 · 210 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-shikra-unleashing-multimodal-llm-s/)
26. [**MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning arXiv:2310.09478**Jun Chen, Deyao Zhu, Xiaoqian Shen, et al.*2023 · 199 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-minigpt-v2-large-language-model/)
27. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency arXiv:2508.18265**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
28. [**ERNIE-ViL: Knowledge Enhanced Vision-Language Representations Through Scene Graph arXiv:2006.16934**Fei Yu, Jiji Tang, Weichong Yin, et al.*2020 · 152 citations*](https://md.research.elamur.ai/free/en/papers/yu-2020-ernie-vil-knowledge-enhanced/)
29. [**GPT-4V(ision) is a Generalist Web Agent, if Grounded arXiv:2401.01614**Boyuan Zheng, Boyu Gou, Jihyung Kil, et al.*2024 · 146 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2024-gpt-4v-ision-generalist-web/)
30. [**PaliGemma: A versatile 3B VLM for transfer arXiv:2407.07726**Lucas Beyer, Andreas Steiner, Andre Susano Pinto, et al.*2024 · 142 citations*](https://md.research.elamur.ai/free/en/papers/beyer-2024-paligemma-versatile-3b-vlm-transfer/)
31. **[Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs](https://md.research.elamur.ai/free/en/papers/bugliarello-2021-multimodal-pretraining-unmasked-meta-analysis/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Emanuele Bugliarello, Ryan Cotterell, Naoaki Okazaki, et al.*2021 · 141 citations*
32. [**DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding arXiv:2412.10302**Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-deepseek-vl2-mixture-experts/)
33. [**Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V arXiv:2310.11441**Jianwei Yang, Hao Zhang, Feng Li, et al.*2023 · 137 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-set-mark-prompting-unleashes-extraordinary/)
34. **[Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/shao-2024-visual-cot-advancing-multi-modal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hao Shao, Shengju Qian, Han Xiao, et al.*2024 · 117 citations*
35. **[LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-lmms-eval-reality-check-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaichen Zhang, Bo Li, Peiyuan Zhang, et al.*2025 · 115 citations*
36. **[Unified Pragmatic Models for Generating and Following Instructions](https://md.research.elamur.ai/free/en/papers/fried-2018-unified-pragmatic-models-generating-following/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Daniel Fried, Jacob Andreas, Dan Klein*2018 · 115 citations*
37. [**GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning arXiv:2507.01006**GLM-V Team, Wenyi Hong, Wenmeng Yu, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-v-glm-4-5v-glm/)
38. **[A Natural Language Corpus of Common Grounding under Continuous and Partially-Observable Context](https://md.research.elamur.ai/free/en/papers/udagawa-2019-natural-language-corpus-common-grounding/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Takuma Udagawa, Akiko Aizawa*2019 · 68 citations*
39. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/)
40. [**DeepSeek-OCR: Contexts Optical Compression arXiv:2510.18234**Haoran Wei, Yaofeng Sun, Yukun Li*2025 · 54 citations*](https://md.research.elamur.ai/free/en/papers/wei-2025-deepseek-ocr-contexts-optical/)
41. **[Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches](https://md.research.elamur.ai/free/en/papers/fried-2023-pragmatics-language-grounding-phenomena-tasks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Daniel Fried, Nicholas Tomlin, Jennifer Hu, et al.*2023 · 38 citations*
42. [**MiMo-VL Technical Report arXiv:2506.03569**Xiaomi LLM-Core Team, Zihao Yue, Zhenru Lin, et al.*2025 · 33 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-vl-technical-report/)
43. [**Qwen3.5-Omni Technical Report arXiv:2604.15804**Qwen Team*2026 · 29 citations*](https://md.research.elamur.ai/free/en/papers/qwen-team-2026-qwen3-5-omni-technical/)
44. **[Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model](https://md.research.elamur.ai/free/en/papers/geigle-2025-centurio-drivers-multilingual-ability-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gregor Geigle, Florian Schneider, Carolin Holtermann, et al.*2025 · 9 citations*
45. **[This One or That One? A Study on Accessibility via Demonstratives with Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-this-one-or-that-one/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yu Wang, Emmanuele Chersoni, Chu-Ren Huang*2026 · 7 citations*
46. [**MedAraBench: Large-Scale Arabic Medical Question Answering Dataset and Benchmark arXiv:2602.01714**Mouath Abu-Daoud, Leen Kharouf, Omar El Hajj, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/abu-daoud-2026-medarabench-large-scale-arabic-medical/)
47. [**DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression arXiv:2609.19969**DeepSeek-AI, Anyi Xu, B. Li, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2026-deepseek-v4-1-flash/)
48. [**Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale arXiv:2603.25040**Yicheng Zou, Dongsheng Zhu, Lin Zhu, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/zou-2026-intern-s1-pro-scientific/)
49. [**Decoupling Pragmatics: Discriminative Decoding for Referring Expression Generation Proceedings of the Reasoning and Interaction Conference (ReInAct 2021)**Simeon Schüz, Sina Zarrieß*2021 · 3 citations*](https://md.research.elamur.ai/free/en/papers/schuz-2021-decoupling-pragmatics-discriminative-decoding-referring/)
50. [**Baichuan-M3: Modeling Clinical Inquiry for Reliable Medical Decision-Making arXiv:2602.06570**Chengfeng Dou, Fan Yang, Fei Li, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-m3-baichuan-m3-modeling-clinical/)
51. **[CCD: Mitigating Hallucinations in Radiology MLLMs via Clinical Contrastive Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-ccd-mitigating-hallucinations-radiology-mllms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xi Zhang, Zaiqiao Meng, Jake Lever, et al.*2026 · 2 citations*
52. **[MedMCP-Calc: Benchmarking LLMs for Realistic Medical Calculator Scenarios via MCP Integration](https://md.research.elamur.ai/free/en/papers/zhu-2026-medmcp-calc-benchmarking-llms-realistic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yakun Zhu, Yutong Huang, Shengqian Qin, et al.*2026 · 2 citations*
53. **[Mind the Gap: Benchmarking LLM Uncertainty and Calibration with Specialty-Aware Clinical QA and Reasoning-Based Behavioural Features](https://md.research.elamur.ai/free/en/papers/testoni-2026-mind-gap-benchmarking-llm-uncertainty/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Alberto Testoni, Iacer Calixto*2026 · 2 citations*
54. **[Persona Jailbreaking in Large Language Models](https://md.research.elamur.ai/free/en/papers/sandhan-2026-persona-jailbreaking-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jivnesh Sandhan, Fei Cheng, Tushar Sandhan, et al.*2026 · 2 citations*
55. [**Referring Expressions with Rational Speech Act Framework: A Probabilistic Approach**Hieu Le, Taufiq Daryanto, Fabian Zhafransyah, et al.*2022 · 2 citations*](https://md.research.elamur.ai/free/en/papers/le-2022-referring-expressions-rational-speech-act/)
56. **[Beyond the Crowd: LLM-Augmented Community Notes for Governing Health Misinformation](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-crowd-llm-augmented-community/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaying Wu, Zihang Fu, Haonan Wang, et al.*2026 · 1 citation*
57. **[CPTCoder: A Reliable LLM System for Medical Procedure Code Prediction](https://md.research.elamur.ai/free/en/papers/wang-2026-cptcoder-reliable-llm-system-medical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Benlu Wang, Ziyao Shangguan, Kyle Tegtmeyer, et al.*2026 · 1 citation*
58. **[Cross-Lingual Empirical Evaluation of Large Language Models for Arabic Medical Tasks](https://md.research.elamur.ai/free/en/papers/abouzahir-2026-cross-lingual-empirical-evaluation-large/) [Workshop on Linguistic Analysis for Health](https://md.research.elamur.ai/free/en/venues/healing/)**Chaimae Abouzahir, Congbo Ma, Nizar Habash, et al.*2026 · 1 citation*
59. **[EchoVLM: Dynamic Mixture-of-Experts Vision-Language Model for Universal Ultrasound Intelligence](https://md.research.elamur.ai/free/en/papers/she-2026-echovlm-dynamic-mixture-experts-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaoyin She, Ruifang Lu, Lida Chen, et al.*2026 · 1 citation*
60. **[How Robust Are Large Language Models for Clinical Numeracy? An Empirical Study on Numerical Reasoning Abilities in Clinical Contexts](https://md.research.elamur.ai/free/en/papers/nguyen-2026-how-robust-are-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Minh-Vuong Nguyen, Fatemeh Shiri, Zhuang Li, et al.*2026 · 1 citation*
61. **[Modeling Clinical Uncertainty in Radiology Reports: From Explicit Uncertainty Markers to Implicit Reasoning Pathways](https://md.research.elamur.ai/free/en/papers/rabaey-2026-modeling-clinical-uncertainty-radiology-reports/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Paloma Rabaey, Jong Hak Moon, Jung-Oh Lee, et al.*2026 · 1 citation*
62. **[Multi-modal, Multi-task, Multi-criteria Automatic Evaluation with Vision Language Models](https://md.research.elamur.ai/free/en/papers/oi-2026-multi-modal-multi-task-multi/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Masanari Oi, Masahiro Kaneko, Naoaki Okazaki, et al.*2026 · 1 citation*
63. **[Otter at MedExAct2026: Diverse Encoder Ensemble for Medical Decision Span Detection](https://md.research.elamur.ai/free/en/papers/lowphansirikul-2026-otter-medexact2026-diverse-encoder-ensemble/) [BioNLP](https://md.research.elamur.ai/free/en/venues/bionlp/)**Lalita Lowphansirikul, Piyalitt Ittichaiwong*2026 · 1 citation*
64. **[Reasoning or Knowledge: Stratified Evaluation of Biomedical LLMs](https://md.research.elamur.ai/free/en/papers/thapa-2026-reasoning-or-knowledge-stratified-evaluation/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Rahul Thapa, Qingyang Wu, Kevin Wu, et al.*2026 · 1 citation*
65. **[Smart_solutions at MEDIQA-SYNUR 2026: A Multi-Stage LLM Pipeline for Nursing Observation Extraction](https://md.research.elamur.ai/free/en/papers/munjal-2026-smart-solutions-mediqa-synur-2026/) [Workshop on Clinical Natural Language Processing (Clinical NLP) @ LREC](https://md.research.elamur.ai/free/en/venues/clinicalnlp/)**Prateek Munjal*2026 · 1 citation*
66. **[AraMinds at AraHealthQA 2025: A Retrieval-Augmented Generation System for Fine-Grained Classification and Answer Generation of Arabic Mental Health Q&A](https://md.research.elamur.ai/free/en/papers/zaytoon-2025-araminds-arahealthqa-2025-retrieval-augmented/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Mohamed Zaytoon, Ahmed Mahmoud Salem, Ahmed Sakr, et al.*2025 · 1 citation*
67. **[AnchorSeg: Language Grounded Query Banks for Reasoning Segmentation](https://md.research.elamur.ai/free/en/papers/qian-2026-anchorseg-language-grounded-query-banks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Qian, Chuanhang Deng, Qiang Huang, et al.*2026*
68. **[Applicability Condition Extraction for Therapeutic Drug-Disease Relations](https://md.research.elamur.ai/free/en/papers/luo-2026-applicability-condition-extraction-therapeutic-drug/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guanting Luo, Noriki Nishida, Yuji Matsumoto, et al.*2026*
69. **[Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/phan-2026-beyond-reasoning-gains-mitigating-general/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hoang Phan, Xianjun Yang, Yuanshun Yao, et al.*2026*
70. [**Bridging the English-Arabic Medical Knowledge Gap: Targeted Low-Rank Adaptation via Causal Layer Selection arXiv:2608.00207 · Findings of the Association for Computational Linguistics: EMNLP 2026**Chaimae Abouzahir, Musa Khan, Hala Ali-Hassan, et al.*2026*](https://md.research.elamur.ai/free/en/papers/abouzahir-2026-bridging-english-arabic-medical-knowledge/)
71. **[Common Objects Out of Context (COOCo): Investigating Multimodal Context and Semantic Scene Violations in Referential Communication](https://md.research.elamur.ai/free/en/papers/merlo-2026-common-objects-out-context-cooco/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Filippo Merlo, Ece Takmaz, Wenkai Chen, et al.*2026*
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